Distributed query execution frameworks, such as a calculation engine executing calculation scenarios, are increasingly being adopted. Some such frameworks provide that a set of configuration parameters can be managed on a global per server instance level. These configuration parameters can be required to setup and maintain a valid infrastructure such as a maximum size of a calculation scenario cache. In addition, the configuration parameters can specify the effect the execution of calculation scenarios. However, by allowing for the configuration parameters to be managed on a global basis, the parameters cannot be changed for dedicated calculation scenarios or queries because they are applied per server instance.
In a distributed query execution framework, consistency must be kept among configuration settings between servers. Consider for example that the configuration parameters for server A allows for a certain optimization, while the configuration parameters for server B do not permit such an optimization. As a result, the overall query performance would be dependent on which parts of the queries are executed on which of the two servers.
Furthermore, issues can arise when global configuration settings are changed during query runtime. With such a scenario (especially with long running queries), a first portion of them can be executed with the old settings while a second portion can be executed with the new settings, thereby negatively affecting query performance.